Optimization of thin-wall structures using hybrid gravitational search and Nelder-Mead algorithm

2016 ◽  
Vol 58 (1) ◽  
pp. 75-78 ◽  
Author(s):  
Ali Rıza Yıldız ◽  
Enes Kurtuluş ◽  
Emre Demirci ◽  
Betul Sultan Yıldız ◽  
Selçuk Karagöz
Keyword(s):  
Thin Wall ◽  
Wall Structures ◽  
Gravitational Search ◽  
Nelder Mead Algorithm

scholarly journals Automated Reconditioning of Thin Wall Structures Using Robot-Based Laser Powder Coating

2020 ◽  
Vol 12 (4) ◽  
pp. 1477
Author(s):  
Shahram Sheikhi ◽  
Eduard Mayer ◽  
Jochen Maaß ◽  
Florian Wagner
Keyword(s):  
Laser Scanner ◽  
Powder Coating ◽  
Basic Knowledge ◽  
Thin Wall ◽  
Economic Potential ◽  
Financial Investment ◽  
Work Space ◽  
Wall Structures ◽  
Cad Cam ◽  
Relevant Component

Implementing digitalization in the field of production represents a major hurdle for some small- and medium-sized enterprises (SMEs) due to the ensuing demands on employees and, in some cases, the significant financial investment required. The RobReLas research project has developed a system whose purpose is to enable an economical solution to this dilemma for SMEs in the field of automated, robot-based reconditioning of components. A laser scanner was integrated in the robot’s control. The data generated by the scanner are used to mathematically describe the virtual area of the surface to be laser-treated. The scanner recognizes the relevant area within the robot’s predefined work space by defining the maximum length and width of the relevant component. The system then automatically applies predefined and qualified repair strategies in the virtual area. Tests on nickel-based blades demonstrated the system’s economic potential, showing a reduction in reconditioning time of about 70% compared to the conventional reconditioning method. The main advantage of the system is the fact that a basic knowledge of operating robots is sufficient for the attainment of repeatable results. Further, no additional CAD/CAM workstations are required for implementation.

scholarly journals Low-Roughness-Surface Additive Manufacturing of Metal-Wire Feeding with Small Power

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4265
Author(s):  
Bobo Li ◽  
Bowen Wang ◽  
Greg Zhu ◽  
Lijuan Zhang ◽  
Bingheng Lu
Keyword(s):  
Additive Manufacturing ◽  
High Surface ◽  
Deposition Process ◽  
High Energy ◽  
Width Ratio ◽  
Thin Wall ◽  
Small Power ◽  
High Surface Quality ◽  
Wall Structures ◽  
Wire Feed

Aiming at handling the contradiction between power constraint of on-orbit manufacturing and the high energy input requirement of metal additive manufacturing (AM), this paper presents an AM process based on small-power metal fine wire feed, which produces thin-wall structures of height-to-width ratio up to 40 with core-forming power only about 50 W. In this process, thermal resistance was introduced to optimize the gradient parameters which greatly reduces the step effect of the typical AM process, succeeded in the surface roughness (Ra) less than 5 μm, comparable with that obtained by selective laser melting (SLM). After a 10 min electrolyte-plasma process, the roughness of the fabricated specimen was further reduced to 0.4 μm, without defects such as pores and cracks observed. The ultimate tensile strength of the specimens measured about 500 MPa, the relative density was 99.37, and the Vickers hardness was homogeneous. The results show that the proposed laser-Joule wire feed-direct metal deposition process (LJWF-DMD) is a very attractive solution for metal AM of high surface quality parts, particularly suitable for rapid prototyping for on-orbit AM in space.

Laser Metal Deposition of Fe- and Co-Based Shape-Memory Alloys

2021 ◽  
Vol 1161 ◽  
pp. 105-112
Author(s):  
Niklas Sommer ◽  
Gabriel Mienert ◽  
Malte Vollmer ◽  
Christian Lauhoff ◽  
Philipp Krooß ◽  
...  
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Microstructural Evolution ◽  
Microstructural Analysis ◽  
Metal Deposition ◽  
Thin Wall ◽  
Laser Metal Deposition ◽  
Wall Structures ◽  
Iron Based ◽  
First Time

In the present study, Iron-based FeMnAlNi and Cobalt-based CoNiGa shape-memory alloys (SMA) were processed by laser metal deposition for the first time. The materials show susceptibility to cracking upon processing when unheated substrates are employed. Pre-heating of the substrate materials eliminated cracking completely and enabled robust deposition of thin-wall structures. Microstructural analysis using optical microscopy revealed different microstructural evolution for the two materials considered.

Study on Crashworthiness Characteristics of Several Concentric Thin Wall Tubes

2010 ◽  
Author(s):  
Parisa Hosseini Tehrani ◽  
Sajad Pirmohammad
Keyword(s):  
Finite Element ◽  
Optimum Combination ◽  
Thick Wall ◽  
Thin Wall ◽  
Finite Element Program ◽  
Linear Dynamic ◽  
Wall Structures ◽  
Moving Body ◽  
Oblique Loading ◽  
Element Program

There is a growing interest in the use of thin-wall structures as a means of absorbing the kinetic energy of a moving body. Multi-layered thin-wall structures are more efficient and lighter than thick-wall structures, and show better crashworthiness characteristics. In this task, several concentric aluminum thin wall tubes as energy absorber under axial and oblique loading are studied and optimum combination of these tubes is presented. The weight of the tubes is optimized while crashworthiness of tubes is not compromised. The commercial finite element program LS-DYNA that offers non-linear dynamic simulation capabilities was used in this study.

Laser Cladding Forming of Unequal-Height Curved Arc-Shaped Thin-Wall Structures

2017 ◽  
Vol 44 (9) ◽  
pp. 0902005
Author(s):  
邓志强 Deng Zhiqiang ◽  
石世宏 Shi Shihong ◽  
周斌 Zhou Bin ◽  
傅戈雁 Fu Geyan ◽  
王聪 Wang Cong
Keyword(s):  
Laser Cladding ◽  
Thin Wall ◽  
Wall Structures
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